Director of Engineering, AI/ML Phenomics

At GSK we see a world in which advanced applications of machine learning and AI will allow us to develop novel therapies to existing diseases and to quickly respond to emerging or changing diseases with personalized drugs, driving better outcomes at reduced cost with fewer side effects. It is an ambitious vision that will require the development of products and solutions at the cutting edge of machine learning and AI. If that excites you, we'd love to chat.

The AI/ML Phenomics team applies advances in machine learning and AI methodologies to high dimensional imaging readouts of high-throughput screens, enabling rich image-based phenotypes of genetic and small-molecule perturbations. These phenotypes, and supporting tools and services, can be leveraged at various stages of the drug discovery pipeline. This is a high impact organization at the intersection of computer vision and life sciences that is critical to our strategy for accelerating and scaling the preclinical pipeline.

This is a director level role with high visibility and growth potential. This is a technical management track role with responsibility for direct reports. Competitive candidates will have a track record of high output leadership as well as experience shipping machine learning products in production. Equally important will be excellent communication, interpersonal and organizational skills, and the ability to represent and transmit the values and principles of our AIML team.

The candidate should be comfortable being accountable for setting the direction, standards and culture of a high performing machine learning engineering team, with demonstrable expertise across machine learning, software engineering and computer vision. Candidates with expertise in high throughput phenotypic screening will be highly competitive. Equally important will be excellent communication, interpersonal and organisational skills, and the ability to represent and transmit the values and principles of our AI/ML team.

The AI/ML team is built on the principles of ownership, accountability, continuous development, and collaboration. We hire for the long term, and we're motivated to make this a great place to work. Our leaders will be committed to your career and development from day one.

As aDirector of AI/ML Engineering, you will:

• Lead a machine learning engineering team responsible for developing and deploying production services to extract insights from high content phenotypic screens

• Manage complex, multi-quarter, cross-functional projects

• Engage with stakeholders from a variety of scientific and engineering disciplines to deliver business impact

• Be a standard bearer for machine learning and software engineering best practices within the organization

• Develop plans to meet requirements, organize a team capable of executing the plans, and lead and track delivery.

• Drive an interview process to enable team growth adhering to diversity and inclusion requirements

• Maintain a safe and inclusive team environment in which people thrive

• Operate in a transparent way, communicating clearly and accurately to leadership and the broader organization

• Develop a high-performing team through coaching, feedback and ensuring opportunities for growth

Basic Qualifications:

• Graduate studies in Computer Science, or undergraduate studies in Computer Science with relevant graduate studies in the life sciences with a focus on AI/ML techniques

• Track record as an independent contributor capable of end-to-end development of ML-powered products for computer vision applications

• Advanced Python programming skills and a track record of delivering robust software solutions

• 2+ years' experience in a technical lead or engineering manager role with direct reports

• 5+ years' experience of professional software development practices: code standards, code review, version control, CI/CD, testing, documentation, Agile, with the ability to mentor others in these practices

• 5+ years with standard deep learning algorithms and model architectures

• In depth knowledge 5+ years in machine learning best practices, scalable training and deployment

Preferred Qualifications:

• PhD in Computer science

• Expertise in high content imaging and/or phenotypic platforms

• Experience shipping large scale data products, APIs, and services

• A track record of developing leaders

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